Using beta binomials to estimate classification uncertainty for ensemble models-Reference-Cited by-同舟云学术

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Using beta binomials to estimate classification uncertainty for ensemble models

Published:2014-06-22 Issue:1 Volume:6 Page:
ISSN:1758-2946
Container-title:Journal of Cheminformatics
language:en
Short-container-title:J Cheminform

Author:

Clark Robert D,Liang Wenkel,Lee Adam C,Lawless Michael S,Fraczkiewicz Robert,Waldman Marvin

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Computer Graphics and Computer-Aided Design,Physical and Theoretical Chemistry,Computer Science Applications

Link

http://link.springer.com/article/10.1186/1758-2946-6-34/fulltext.html

Reference35 articles.

1. Eriksson L, Jaworska J, Worth AP, Cronin MTD, McDowell RM, Gramatica P: Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs. Environ Health Perspect. 2003, 111: 1361-1375.

2. Worth AP: The role of QSAR methodology in the regulatory assessment of chemicals. Advances in Computational Chemistry and Physics Volume 8: Recent Advances in QSAR Studies. Edited by: Puzyn T, Leszczynski J, Cronin MT. 2010, Netherlands: Springer, 367-

3. Sahlin U: Uncertainty in QSAR Predictions. Altern Lab Anim. 2013, 41: 111-125.

4. Weaver S, Gleeson MP: The importance of the domain of applicability in QSAR modeling. J Mol Graph Model. 2008, 26: 1315-1326.

5. Tong W, Xie Q, Hong H, Shi L, Fang H, Perkins R: Assessment of prediction confidence and domain extrapolation of two structure–activity relationship models for predicting estrogen receptor binding activity. Environ Health Perspect. 2004, 112: 1249-1254.

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